Design a statistically rigorous A/B test or product experiment with a clear hypothesis, success metrics, sample size, guardrails, and a decision rule to avoid common experimentation pitfalls.
## CONTEXT Experimentation is how mature product teams replace opinion with evidence, but a poorly designed A/B test is worse than no test because it produces confident, wrong conclusions that drive bad decisions at scale. The discipline of good experimentation lies in forming a falsifiable hypothesis, choosing a…
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